Referanslar:
çoklu etiket
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:told-br/multilabel')
- Tanım :
ToLD-Br is the biggest dataset for toxic tweets in Brazilian Portuguese, crowdsourced
by 42 annotators selected from a pool of 129 volunteers. Annotators were selected aiming
to create a plural group in terms of demographics (ethnicity, sexual orientation, age, gender).
Each tweet was labeled by three annotators in 6 possible categories:
LGBTQ+phobia,Xenophobia, Obscene, Insult, Misogyny and Racism.
- Lisans : https://github.com/JAugusto97/ToLD-Br/blob/main/LICENSE_ToLD-Br.txt
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 21000 |
- Özellikler :
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"homophobia": {
"num_classes": 4,
"names": [
"zero_votes",
"one_vote",
"two_votes",
"three_votes"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"obscene": {
"num_classes": 4,
"names": [
"zero_votes",
"one_vote",
"two_votes",
"three_votes"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"insult": {
"num_classes": 4,
"names": [
"zero_votes",
"one_vote",
"two_votes",
"three_votes"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"racism": {
"num_classes": 4,
"names": [
"zero_votes",
"one_vote",
"two_votes",
"three_votes"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"misogyny": {
"num_classes": 4,
"names": [
"zero_votes",
"one_vote",
"two_votes",
"three_votes"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"xenophobia": {
"num_classes": 4,
"names": [
"zero_votes",
"one_vote",
"two_votes",
"three_votes"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
ikili
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:told-br/binary')
- Tanım :
ToLD-Br is the biggest dataset for toxic tweets in Brazilian Portuguese, crowdsourced
by 42 annotators selected from a pool of 129 volunteers. Annotators were selected aiming
to create a plural group in terms of demographics (ethnicity, sexual orientation, age, gender).
Each tweet was labeled by three annotators in 6 possible categories:
LGBTQ+phobia,Xenophobia, Obscene, Insult, Misogyny and Racism.
- Lisans : https://github.com/JAugusto97/ToLD-Br/blob/main/LICENSE_ToLD-Br.txt
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'test' | 2100 |
'train' | 16800 |
'validation' | 2100 |
- Özellikler :
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 2,
"names": [
"not-toxic",
"toxic"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}